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Showing 1 to 15 of 17 results Save | Export
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Sarah Klevan; Melanie Leung-Gagné; Tomoko M. Nakajima – Learning Policy Institute, 2024
Across the United States, there is an increased interest in improving school climate, reflecting a deepening understanding of the foundational role that school climate can play in supporting students' well-being, learning, and development. School climate is constructed from norms, expectations, and interpersonal relationships that come together to…
Descriptors: Educational Environment, Middle Schools, School Districts, Data Use
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Jenna Howard Terrell; Christopher C. Henrich; Ryan Miskell; Amanda Nabors; Kathryn Grogan; Joseph McCrary – Contemporary School Psychology, 2025
State and local education agencies continue to make an effort to systematically assess school climate through student surveys. These assessments typically collect data from individual students about their perceptions of different components of the school and their relationship to individuals in the school and aggregate those responses to the…
Descriptors: Educational Environment, School Districts, State Agencies, Student Attitudes
Office for Civil Rights, US Department of Education, 2025
The 2021-22 Civil Rights Data Collection (CRDC) is a mandatory survey of all public school districts and schools serving students in preschool through grade 12 in the 50 states, Washington, D.C., and the Commonwealth of Puerto Rico and therefore includes data from 17,704 public school districts also known as local education agencies (LEAs) and…
Descriptors: Public Schools, School Districts, Data Collection, Access to Education
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Wang, Karen D.; Cock, Jade Maï; Käser, Tanja; Bumbacher, Engin – British Journal of Educational Technology, 2023
Technology-based, open-ended learning environments (OELEs) can capture detailed information of students' interactions as they work through a task or solve a problem embedded in the environment. This information, in the form of log data, has the potential to provide important insights about the practices adopted by students for scientific inquiry…
Descriptors: Data Use, Educational Environment, Science Process Skills, Inquiry
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A. Corinne Huggins-Manley; Jing Huang; Jerri-ann Danso; Wei Li; Walter L. Leite – Journal of Experimental Education, 2024
The global COVID-19 health pandemic caused major interruptions to educational assessment systems, partially due to shifts to remote learning environments, entering the post-COVID educational world into one that is more open to heterogeneity in instructional and assessment modes for secondary students. In addition, in 2020, educational inequities…
Descriptors: Student Evaluation, Educational Environment, Educational Change, COVID-19
A. Corinne Huggins-Manley; Jing Huang; Jerri-ann Danso; Wei Li; Walter L. Leite – Grantee Submission, 2023
The global COVID-19 health pandemic caused major interruptions to educational assessment systems, partially due to shifts to remote learning environments, entering the post-COVID educational world into one that is more open to heterogeneity in instructional and assessment modes for secondary students. In addition, in 2020, educational inequities…
Descriptors: Student Evaluation, Educational Environment, Educational Change, COVID-19
Luke Keele; Matthew Lenard; Lindsay Page – Annenberg Institute for School Reform at Brown University, 2021
In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…
Descriptors: Cluster Grouping, Educational Environment, Outcomes of Treatment, Compliance (Psychology)
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Martin, Caitlin K.; Nacu, Denise; Pinkard, Nichole – Journal of Learning Analytics, 2016
Online environments can cultivate what have been referred to as 21st century skills and capabilities, as youth contribute, pursue, share, and interact around work and ideas. Such environments also hold great potential for addressing digital divides related to the development of such skills by connecting youth in areas with fewer resources and…
Descriptors: Data Collection, Data Interpretation, Creativity, Socialization
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Seifert, Tricia A.; Goodman, Kathleen; King, Patricia M.; Baxter Magolda, Marcia B. – Journal of Mixed Methods Research, 2010
This study details the collection, analysis, and interpretation of data from a national multi-institutional longitudinal mixed methods study of college impact and student development of liberal arts outcomes. The authors found three sets of practices in the quantitative data that corroborated with the themes that emerged from the qualitative data:…
Descriptors: Student Development, Liberal Arts, Content Analysis, Data Interpretation
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Shin, Jongho; Lee, Hyunjoo; Kim, Yongnam – School Psychology International, 2009
The purpose of the study was to comparatively investigate student- and school-level factors affecting mathematics achievement of Korean, Japanese and American students. For international comparisons, the PISA 2003 data were analysed by using the Hierarchical Linear Modeling method. The variables of competitive-learning preference, instrumental…
Descriptors: Mathematics Achievement, Foreign Countries, Comparative Education, Performance Factors
Furtwengler, Willis J.; Micich, Anita – 1991
A study examined the nature of school culture information found in symbolic pictures of schools. One specific goal was to determine the nature of school culture information embedded in verbal interpretations of symbolic school drawings and the accuracy of reviewers' interpretations of the drawings. Another goal was to compare information from the…
Descriptors: Data Interpretation, Educational Environment, Elementary Secondary Education, Institutional Characteristics
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Armstrong, Robert L.; Dusseau, Deborah Jeffries – Journal of School Improvement, 2001
Analyzes two possible assessment outcomes: (1) differing results on two or more assessments; and (2) loss of achievement after improvement cycle. Proposes short- and long-term solutions to problematic results, including analyzing differences in tests and pre-planning to avoid flaws in assessment design. (NB)
Descriptors: Data Interpretation, Differences, Educational Environment, Educational Objectives
Kaufman, Phillip; Chen, Xianglei; Choy, Susan P.; Peter, Katharin; Ruddy, Sally A.; Miller, Amanda K.; Fleury, Jill K.; Chandler, Kathryn A.; Plany, Michael G.; Rand, Michael R. – 2001
This report, the fourth in a series of annual reports on school crime, presents the latest available data on school crime and student safety. National indicators affirm that the levels of crime in school have continued to decline, that acts that promote fear and detract from learning are decreasing, and that students feel safer in school than they…
Descriptors: Crime, Data Analysis, Data Interpretation, Death
DeVoe, Jill F.; Peter, Katharin; Kaufman, Phillip; Ruddy, Sally A.; Miller, Amanda K.; Planty, Mike; Snyder, Thomas D.; Duhart, Detis T.; Rand, Michael R. – 2002
This report, the fifth in a series of annual reports on school crime, presents the latest available data on school crime and student safety. The data present a mixed picture of school safety. Rates of criminal victimization in school have declined or remained constant, and students seem to feel more secure at school than they did a few years ago.…
Descriptors: Crime, Data Analysis, Data Interpretation, Death
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Liu, Min; Bera, Stephan – Educational Technology Research and Development, 2005
In this study, we examined the use of cognitive tools provided in a problem-based hypermedia learning environment for sixth graders. Purposes were to understand how the built-in tools were used, and if tool use was associated with different problem-solving stages. Results showed that tools supporting cognitive processing and sharing cognitive load…
Descriptors: Grade 6, Educational Environment, Problem Solving, Hypermedia
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